The differences between SAP R3 and S4 HANA – and how SAP automates pricing.

Artificial intelligence (AI) is a rapidly developing field that has the potential to revolutionise B2B sales. One of the companies at the forefront of AI adoption is SAP, a global software corporation that provides enterprise software (ERP) to manage business operations and customer relations.

In this blog post, we will explore the role of AI in SAP’s products and services and discuss how the company uses AI to automate pricing and sales analytics.

We will also examine the differences between SAP R3 and S4 HANA and the process of migrating from SAP ECC to S4 HANA. In addition, we will consider the benefits of using external providers of AI rather than relying solely on native SAP modules.

Does SAP use artificial intelligence?

Yes, SAP uses artificial intelligence in many of its products and services. One example is SAP Leonardo, a suite of digital innovation systems that combines various technologies, including AI, the Internet of Things (IoT), and big data analytics, to help businesses transform and become more agile. SAP Leonardo includes various AI-powered tools, such as machine learning algorithms, natural language processing, and image recognition, that can automate tasks and improve decision-making.

Another example of SAP’s use of AI is the SAP Predictive Analytics solution, which uses machine learning algorithms to analyse data and predict future outcomes. Industrial distributors and manufacturers with thousands of products in stock can use Predictive Sales for various purposes, such as predicting customer churn, detecting cross-selling potential, and optimising pricing.

SAP is leveraging AI to automate its pricing. For example, the company’s “Automate SAP Pricing Policy” tool uses machine learning algorithms to analyse market data and customer behaviour and then generates personalised pricing recommendations for each customer. AI helps businesses to optimise their pricing strategies and increase profitability.

While these native SAP modules can be effective in providing AI-powered solutions, it is worth considering the benefits of using external providers of AI as well. One advantage of external providers is that they often have specialised expertise and experience in a particular area of AI, such as B2B Sales.

Employing external AI Software can accelerate the implementation of AI in SAP while significantly reducing costs. In addition, external providers can offer more flexible pricing and deployment options, as well as ongoing support and maintenance services. Furthermore, as of the last HANA release, some SAP Predictive apps are obsolete. Migrating to HANA means that controllers need to re-write predictive scenarios with the Intelligent Scenario Lifecycle Management (ISLM) – the new SAP machine learning management framework.

Tables MVKE and KONDM in SAP – Make them predictive.

One current challenge for companies using SAP and migrating withing the SAP family is the manual maintenance of the MVKE (Material master data) and KONDM (Condition master data) tables – both essential for maintaining and managing pricing information. The MVKE table stores material-specific data, such as the material number, unit of measure, and base price. The KONDM table, on the other hand, stores condition-specific data, such as discounts, surcharges, and different pricing conditions.

To maintain the MVKE table, you will need to create and maintain material master records containing all the relevant data for a specific material. Usually, sales controllers do this through the SAP transaction code MM01 (Create Material). One can also use the SAP transaction code MM02 (Change Material) to change an existing material master record.

To maintain the KONDM table, you must create and sustain condition records containing all the relevant data for a specific pricing condition. SAP Analysts or controllers can perform this task using the SAP transaction code VK11 (Create Condition). One can also use the SAP transaction code VK12 (Change Condition) to change an existing condition record.

In B2B wholesaling and distribution, it is essential to regularly maintain the MVKE and KONDM tables to ensure that your pricing information is up-to-date and accurate. This is one of the main reasons to make them predictive using AI.

Difference between SAP R3 and S4 HANA – Step by Step

If you are currently using SAP ECC and are considering upgrading to S4 HANA, you will need to go through a process called SAP ECC to S4 HANA migration. This process involves transferring all your data and customisations from SAP ECC to S4 HANA and testing and verifying that everything is working correctly in the new system. It is essential to carefully plan and execute the migration process to ensure a smooth transition and minimise disruption to your business operations.

Moreover, most SAP customers will be forced to change ERP software by the year 2027 at the lattest. At that time, support for previous software versions will be discontinued, forcing SAP customers to search for a new solution. SAP pushes now HANA as its flagship ERP.

One key difference between SAP R3 and S4 HANA is that S4 HANA is a more modern and advanced ERP system. It offers in-memory technology, which allows for faster processing of large amounts of data. S4 HANA also includes a range of new features and capabilities not available in SAP R3, such as real-time and advanced predictive analytics.

Historically, B2B wholesalers and manufacturers employ SAP sales analytics to identify growth opportunities, optimise pricing strategies, and improve customer relationships. Sales analytics is vital to all ERP systems, including S4 HANA.

SAP data mining is another essential feature of S4 HANA. It allows businesses to analyse and extract valuable data insights using advanced algorithms and machine learning (ML) techniques. AI and ML can identify trends and patterns that may not be immediately visible to humans, helping businesses to make more informed decisions and drive better business outcomes.


Artificial Intelligence in SAP ECC & S4 HANA – Conclusion

Artificial intelligence (AI) is a priceless tool for businesses using SAP’s enterprise resource planning (ERP) system. SAP’s AI-powered solutions, such as SAP Leonardo and SAP Predictive Analytics, can automate tasks, improve decision-making, and optimise pricing strategies.

However, using external AI providers can offer additional benefits, including specialised expertise, cost savings, and flexible deployment options. There are challenges in using SAP AI, such as the manual maintenance of essential data tables. Still, external AI providers can help to make these tables more predictive and improve accuracy and efficiency.

Migrating from SAP ECC to S4 HANA, the more modern and advanced version of SAP’s ERP system, involves transferring data, customisations, testing, and verifying that everything is working correctly. Overall, using external AI in an ERP system like SAP can help businesses to drive better business outcomes and stay competitive.


Further Read:

SAP Help Portal: Predictive Analytics Integrator (PAI)